Hepatocellular Carcinoma (HCC) represents the third most common cause of cancer death in the world and the incidence of HCC is rising in the United States. Only 15% of HCC patients are eligible for surgical intervention, and resistance to chemotherapy, high relapse rates and poor prognosis are common features of HCC. Epithelial-to-mesenchymal transition (EMT) is a process initiated during liver development that is utilized by liver cancer cells to initiate metastatic spread. After EMT, liver epithelial cells become motile, mesenchymal cells and lose cell-to-cell adhesion, which allows for the migration from the primary tumor site. Understanding EMT is critical to HCC and other cancer patients as the primary cause of cancer related mortality in 90% of cases is metastatic disease. Recently, we have demonstrated that Hepatocyte Growth Factor (HGF) is a primary initiator of EMT in multiple liver cancer models. HGF is a potent growth factor for hepatocytes and binds to high-affinity receptor c-Met. In HCC, c-Met tyrosine kinase phosphorylation results in down-stream activation of multiple signal cascades, ultimately driving tumor proliferation, survival, invasion, and metastasis. The specific objective of this proposal is to utilize network theory and dynamic modeling with direct in vitro and in vivo laboratory analysis to assess the role of hepatocyte growth factor (HGF) as a primary inducer of EMT and to understand the role of Snail in maintaining the EMT phenotype in metastatic disease. The central hypothesis is that HGF is required for induction of EMT and that Snail is a critical node for maintenance of EMT in liver cancer. As presented in Preliminary Studies, we have demonstrated that HGF- induced EMT results in increased metastasis in vivo. We have validated our murine models using human HCC transcriptome profiles from the NCI. Within metastatic tumors from murine models and human HCC cells, the mesenchymal cancer cells demonstrated up-regulated Zeb1, Zeb2, and Snail, and loss of E-cadherin and microRNA 200b. In an effort to reverse EMT with forced up-regulation of microRNA 200b, we demonstrated a reversal of mesenchymal characteristics in vitro without a decreased metastatic potential in vivo. To better understand these discongruous results, we constructed an EMT signaling network and utilized dynamic Boolean modeling. We identified that Snail is a critical node for maintaining a mesenchymal/metastatic phenotype post EMT. The rationale for the proposed research is that network modeling provides a unique means to identify critical regulators of complex biological processes. Through identification of the critical regulators of EMT in liver cancer metastasis, we will identify the major contributors to metastasis. The proposed work is innovative as we capitalize on network modeling to rationally identify critical nodes within the EMT pathway, and then we propose model verification using human and murine HCC cell lines with in vitro and in vivo assessment of mesenchymal phenotype and metastatic potential. We expect that the proposed model will produce novel critical targets for potential prevention and/or treatment of metastatic HCC.